IT Advisor - Technology Cons - AI and Data - Data Science - Manager - Multiple Positions - 1703399

About EY-Parthenon•Chicago, IL

5d•Hybrid

About The Position

EY focuses on high-ethical standards and integrity among its employees and expects all candidates to demonstrate these qualities. At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better. Join us and build an exceptional experience for yourself, and a better working world for all. The exceptional EY experience. It's yours to build. Work with a wide variety of clients to deliver the latest data science technologies and operations research techniques and practices to design, build and maintain scalable and robust solutions that unify, enrich and analyze data from multiple sources. Assist clients to make data-driven decisions by working with structured and unstructured data sets, building out predictive models, and advising our clients on data mining leading practices. Manage and contribute to development of proof of concepts and/or pilots for clients while working in cross-functional teams. Leverage in-house data platforms as needed and recommending and building new data platforms/solutions as required to exceed business requirements. Manage and motivate teams with diverse skills and backgrounds. Consistently deliver quality client services by monitoring progress. Demonstrate in-depth technical capabilities and professional knowledge. Maintain long-term client relationships and networks. Cultivate business development opportunities.

Requirements

Bachelor's degree in Mathematics, Information Systems, Statistics, Operations Research, Analytics, Computer Science, Data Science, Machine Learning, or a related field and 5 years of progressive, post-baccalaureate related work experience.
Alternatively, a Master's degree in Mathematics, Information Systems, Statistics, Operations Research, Analytics, Computer Science, Data Science, Machine Learning, or a related field and 4 years of related work experience.
Experience may be gained as part of the required education, including co-op and/or internship experience.
4 years of professional services and/or consulting experience.
4 years of hands-on experience in data science, including its applications in business for client conversations.
2 years of experience in concepts in big data and data engineering.
4 years of experience in a combination involving at least two of the following: R, Python, SQL, SAS or similar in core packages and libraries used for data science and machine learning.
4 years of experience in a combination involving at least two of the following: ETL and data engineering skills, including data cleansing and manipulation using SQL based tool/platforms.
4 years of experience in a combination involving at least two of the following: Data sources and structures using one or a combination of the following: APIs, NoSQL, RDBMS, Hadoop, S3, Blob Storage, and/or similar.
4 years of experience in a combination involving at least two of the following: Big data technologies in one or a combination of the following ecosystems: Hadoop, AWS and/or Microsoft.
2 years of experience managing teams of Data and Analytics professionals.

Responsibilities

Design, build and maintain scalable and robust solutions that unify, enrich and analyze data from multiple sources.
Assist clients to make data-driven decisions by working with structured and unstructured data sets, building out predictive models, and advising our clients on data mining leading practices.
Manage and contribute to development of proof of concepts and/or pilots for clients while working in cross-functional teams.
Leverage in-house data platforms as needed and recommending and building new data platforms/solutions as required to exceed business requirements.
Manage daily operations of a global data and analytics team(s) on client engagements, review developed models, provide feedback, and assist in model development and data analysis.
Manage other data scientists and data engineers to develop and deliver the most appropriate algorithms to meet client requirements.
Build and apply data analysis algorithms and design, architect, and develop solutions leveraging big data technology to ingest, process, and analyze large, disparate data sets to meet or exceed business requirements.
Communicate findings, recommendations, and opportunities to facilitate client presentations and/or improve data systems and solutions.
Manage and motivate teams with diverse skills and backgrounds.
Consistently deliver quality client services by monitoring progress.
Demonstrate in-depth technical capabilities and professional knowledge.
Maintain long-term client relationships and networks.
Cultivate business development opportunities.